“Technological advances for the detection of pre-analytical errors in the clinical laboratory: a systematic review”
DOI:
https://doi.org/10.70577/asce.v5i3.1048Keywords:
preanalytical phase; clinical laboratory; automation; artificial intelligence; preanalytical errors; diagnostic quality.Abstract
The pre-analytical phase of the clinical laboratory is considered the most vulnerable stage of the diagnostic process due to the high frequency of errors associated with patient identification and the collection, handling, transportation, and storage of biological samples. These errors compromise the reliability of laboratory results and represent a significant risk to patient safety. The aim of this systematic review was to analyze technological advances applied to the pre-analytical phase of the clinical laboratory and their impact on error detection and reduction. The study was conducted in accordance with PRISMA guidelines through a comprehensive literature search of PubMed, ScienceDirect, PubMed Central, and regional scientific journals. A total of 23 studies published between 2020 and 2025 related to technologies applied in the pre-analytical phase were included. The findings revealed that the main technologies implemented were automated systems, barcode identification systems, laboratory information systems (LIS), and artificial intelligence. The most frequently reported pre-analytical errors included hemolysis, patient misidentification, inadequate labeling, and sample transportation errors. The analyzed studies consistently demonstrated that the implementation of these technologies improves sample traceability, reduces manual intervention, enhances diagnostic quality, and strengthens patient safety. In conclusion, the integration of advanced technologies into the pre-analytical phase represents a fundamental strategy for reducing errors and optimizing clinical laboratory processes.
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